Replay across Experiments: A Natural Extension of Off-Policy RL.
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Proceedings of the Twelfth International Conference on Learning Representations, 2024
Generative Adversarial Equilibrium Solvers.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning.
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Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024
Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football".
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Dataset, August, 2022
A Generalized Training Approach for Multiagent Learning.
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Proceedings of the 8th International Conference on Learning Representations, 2020
Biases for Emergent Communication in Multi-agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems.
Proceedings of the 2019 Conference on Artificial Life, 2019
Emergent Coordination Through Competition.
Proceedings of the 7th International Conference on Learning Representations, 2019
The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.
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CoRR, 2018
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.
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Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018
Value-Decomposition Networks For Cooperative Multi-Agent Learning.
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CoRR, 2017
Nesterov's accelerated gradient and momentum as approximations to regularised update descent.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
Approximate Newton Methods for Policy Search in Markov Decision Processes.
J. Mach. Learn. Res., 2016
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
A Gauss-Newton Method for Markov Decision Processes.
CoRR, 2015
Modelling Policies in MDPs in Reproducing Kernel Hilbert Space.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
Deterministic Policy Gradient Algorithms.
Proceedings of the 31th International Conference on Machine Learning, 2014
Tighter PAC-Bayes bounds through distribution-dependent priors.
Theor. Comput. Sci., 2013
Data dependent kernels in nearly-linear time.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Conditional mean embeddings as regressors - supplementary
CoRR, 2012
Conditional mean embeddings as regressors.
Proceedings of the 29th International Conference on Machine Learning, 2012
Modelling transition dynamics in MDPs with RKHS embeddings.
Proceedings of the 29th International Conference on Machine Learning, 2012
Exploiting structure defined by data in machine learning : some new analyses.
PhD thesis, 2011
Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Distribution-Dependent PAC-Bayes Priors.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010
Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation.
Proceedings of the COLT 2009, 2009
Online Prediction on Large Diameter Graphs.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008